Application of the LDM algorithm to identify small lung nodules on low-dose MSCT scans Conference Paper
| Authors: | Zhao, B.; Ginsberg, M. S.; Lefkowitz, R. A.; Jiang, L.; Cooper, C.; Schwartz, L. H. |
| Editors: | Fitzpatrick, J. M.; Sonka, M. |
| Title: | Application of the LDM algorithm to identify small lung nodules on low-dose MSCT scans |
| Conference Title: | Progress in Biomedical Optics and Imaging - Medical Imaging 2004: Imaging Processing |
| Abstract: | In this work, we present a computer-aided detection (CAD) algorithm for small lung nodules on low-dose MSCT images. With this technique, identification of potential lung nodules is carried out with a local density maximum (LDM) algorithm, followed by reduction of false positives from the nodule candidates using task-specific 2-D/3-D features along with a knowledge-based nodule inclusion/exclusion strategy. Twenty-eight MSCT scans (40/80mAs, 120kVp, 5mm collimation/2.5mm reconstruction) from our lung cancer screening program that included at least one lung nodule were selected for this study. Two radiologists independently interpreted these cases. Subsequently, a consensus reading by both radiologists and CAD was generated to define a "gold standard". In total, 165 nodules were considered as the "gold standard" (average: 5.9 nodules/case; range: 1-22 nodules/case). The two radiologists detected 146 nodules (88.5%) and CAD detected 100 nodules (60.6%) with 8.7 false-positives/case. CAD detected an additional 19 nodules (6 nodules ≥ 3mm and 13 nodules < 3mm) that had been missed by both radiologists. Preliminary results show that the CAD is capable of detecting small lung nodules with acceptable number of false-positives on low-dose MSCT scans and it can detect nodules that are otherwise missed by radiologists, though a majority are small nodules (< 3mm). |
| Keywords: | computerized tomography; tumors; image processing; blood vessels; personnel; computed tomography (ct); computer aided diagnosis; pulmonary diseases; computer-aided detection (cad); local density maximum; small lung nodule; image sets; multiple thresholding |
| Journal Title | Proceedings of SPIE |
| Volume: | 5370 |
| Conference Dates: | 2004 Feb 14 |
| Conference Location: | San Diego, CA |
| ISBN: | 0277-786X |
| Publisher: | SPIE |
| Date Published: | 2004-05-12 |
| Start Page: | 818 |
| End Page: | 823 |
| Language: | English |
| DOI: | 10.1117/12.535558 |
| PROVIDER: | scopus |
| DOI/URL: | |
| Notes: | Proc SPIE Int Soc Opt Eng -- Conference code: 63695 -- Cited By (since 1996):8 -- Export Date: 16 June 2014 -- CODEN: PSISD -- 16 February 2004 through 19 February 2004 -- Source: Scopus |
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